- 专利标题: Convolution-Augmented Transformer Models
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申请号: US17139525申请日: 2020-12-31
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公开(公告)号: US20220207321A1公开(公告)日: 2022-06-30
- 发明人: Anmol Gulati , Ruoming Pang , Niki Parmar , Jiahui Yu , Wei Han , Chung-Cheng Chiu , Yu Zhang , Yonghui Wu , Shibo Wang , Weikeng Qin , Zhengdong Zhang
- 申请人: Google LLC
- 申请人地址: US CA Mountain View
- 专利权人: Google LLC
- 当前专利权人: Google LLC
- 当前专利权人地址: US CA Mountain View
- 主分类号: G06N3/04
- IPC分类号: G06N3/04 ; G10L15/16 ; G06N20/00
摘要:
Systems and methods can utilize a conformer model to process a data set for various data processing tasks, including, but not limited to, speech recognition, sound separation, protein synthesis determination, video or other image set analysis, and natural language processing. The conformer model can use feed-forward blocks, a self-attention block, and a convolution block to process data to learn global interactions and relative-offset-based local correlations of the input data.
公开/授权文献
- US12079703B2 Convolution-augmented transformer models 公开/授权日:2024-09-03
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